{"id":"https://openalex.org/W3192047529","doi":"https://doi.org/10.1109/tits.2021.3101530","title":"Exploring Patterns of Train Delay Evolution and Timetable Robustness","display_name":"Exploring Patterns of Train Delay Evolution and Timetable Robustness","publication_year":2021,"publication_date":"2021-08-10","ids":{"openalex":"https://openalex.org/W3192047529","doi":"https://doi.org/10.1109/tits.2021.3101530","mag":"3192047529"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3101530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3101530","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072822465","display_name":"Mehmet \u015eirin Artan","orcid":"https://orcid.org/0000-0002-7983-5961"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Mehmet Sirin Artan","raw_affiliation_strings":["Department of Civil Engineering, Transportation Division, Yildiz Technical University, İstanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Transportation Division, Yildiz Technical University, İstanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049592383","display_name":"\u0130smail \u015eahin","orcid":"https://orcid.org/0000-0002-6959-6215"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ismail Sahin","raw_affiliation_strings":["Department of Civil Engineering, Transportation Division, Yildiz Technical University, İstanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Transportation Division, Yildiz Technical University, İstanbul, Turkey","institution_ids":["https://openalex.org/I4101805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072822465"],"corresponding_institution_ids":["https://openalex.org/I4101805"],"apc_list":null,"apc_paid":null,"fwci":2.2566,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.8934823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"23","issue":"8","first_page":"11205","last_page":"11214"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.8926811218261719},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.7946215867996216},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.6743703484535217},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6699515581130981},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.643548309803009},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.6275547742843628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6000954508781433},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5993016958236694},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16866686940193176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16830477118492126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15514034032821655},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12185966968536377}],"concepts":[{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.8926811218261719},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7946215867996216},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.6743703484535217},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6699515581130981},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.643548309803009},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.6275547742843628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000954508781433},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5993016958236694},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16866686940193176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16830477118492126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15514034032821655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12185966968536377},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2021.3101530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3101530","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W594522087","https://openalex.org/W1493617018","https://openalex.org/W1587383887","https://openalex.org/W1976065452","https://openalex.org/W1988604380","https://openalex.org/W1989265314","https://openalex.org/W1998654411","https://openalex.org/W2007358669","https://openalex.org/W2018855219","https://openalex.org/W2030805284","https://openalex.org/W2033181859","https://openalex.org/W2035729665","https://openalex.org/W2042580362","https://openalex.org/W2046258125","https://openalex.org/W2079246731","https://openalex.org/W2114797900","https://openalex.org/W2134131633","https://openalex.org/W2158193863","https://openalex.org/W2314645870","https://openalex.org/W2522225365","https://openalex.org/W2567414071","https://openalex.org/W2610323442","https://openalex.org/W2618782758","https://openalex.org/W2742989960","https://openalex.org/W2751490822","https://openalex.org/W2757054860","https://openalex.org/W2791079235","https://openalex.org/W2887126012","https://openalex.org/W2891489121","https://openalex.org/W2922805962","https://openalex.org/W2936650651","https://openalex.org/W2964514245","https://openalex.org/W2997073788","https://openalex.org/W4250415028","https://openalex.org/W6617871425","https://openalex.org/W6635106296","https://openalex.org/W6677307935","https://openalex.org/W7011410433"],"related_works":["https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2084326697","https://openalex.org/W2027903142","https://openalex.org/W2354322608","https://openalex.org/W2804608325","https://openalex.org/W2077211377","https://openalex.org/W2186675474","https://openalex.org/W2387462590"],"abstract_inverted_index":{"Uncertainty":[0],"affects":[1],"the":[2,13,24,40,57,65,86,95,121,143,154,159,169,179,200,210,215,221],"overall":[3],"performance":[4,138],"of":[5,19,45,50,68,79,97,124,128,134,199],"railway":[6,98,161,170],"systems.":[7],"It":[8],"can":[9,184],"be":[10,32,185],"captured":[11],"tracking":[12],"successive":[14],"departure":[15,41],"and":[16,42,70,82,105,114,126,145,149,165,178,192,202],"arrival":[17,43],"events":[18,123],"trains":[20,125],"at":[21],"stations":[22],"in":[23,39,73,85,120,158,173],"scheduled":[25],"railways.":[26],"Markov":[27,58,109,147,181],"chains":[28,110],"has":[29],"shown":[30],"to":[31,36,55,94,117,188,193,209],"an":[33],"effective":[34,115],"means":[35],"model":[37,204,217],"variabilities":[38],"delays":[44,119,129,191],"trains.":[46],"The":[47,163,197],"empirical":[48],"data":[49,156,212],"actual":[51,155],"operations":[52,99],"are":[53,205],"used":[54,186],"develop":[56],"matrices.":[59],"Transitions":[60],"between":[61],"delay":[62],"states":[63],"comprise":[64],"internal":[66],"dynamics":[67],"running":[69],"dwelling":[71],"processes":[72],"probabilistic":[74],"terms,":[75],"presenting":[76],"particular":[77],"patterns":[78],"deterioration,":[80],"recovery":[81],"state":[83],"keeping":[84],"prevailing":[87],"timetable":[88,195],"setting.":[89],"All":[90],"these":[91],"features":[92],"conform":[93],"practice":[96],"as":[100,102],"well":[101,177],"train":[103,190],"dispatchers":[104],"drivers.":[106],"Hence,":[107],"delay-based":[108],"becomes":[111],"a":[112,131],"simple":[113,137],"tool":[116],"predict":[118,189],"following":[122],"distribution":[127],"over":[130],"longer":[132],"period":[133],"time":[135],"using":[136,153],"measures.":[139],"We":[140],"have":[141],"developed":[142],"homogeneous":[144,201,222],"non-homogeneous":[146,203,216],"models":[148,183],"tested":[150],"their":[151],"performances":[152],"collected":[157],"Netherlands":[160],"network.":[162],"analysis":[164],"evaluation":[166],"show":[167],"that":[168,214],"corridor":[171],"considered":[172],"this":[174],"study":[175],"performs":[176,218],"corresponding":[180],"chain":[182],"effectively":[187],"evaluate":[194],"robustness.":[196],"outcomes":[198],"evaluated":[206],"with":[207],"respect":[208],"observed":[211],"resulting":[213],"better":[219],"than":[220],"model.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}